Universal Weight Subspace Hypothesis
Description
Superman:
"Researchers proved every AI model on earth is secretly the same model.
They tested 1,100+ different AI models. Vision models. Language models. Code generators.
They had different tasks. Different training data. Completely different starting points.
But when researchers looked inside at the actual mathematical structure of their weights, they found something impossible.
They were all converging into the exact same geometric shape.
They call it Universal Weight Subspace Hypothesis.
No matter what you ask an AI to learn, its high-dimensional brain inevitably collapses into the exact same low-dimensional structure.
The models aren't inventing new ways to understand the world based on the data you feed them.
The structure is already there. Like a mathematical gravity well.
The architecture defines the universe. The training data just pushes the model into the basin.
This changes everything we know about how machine learning actually works."